app.py

import gradio as gr
from transformers import pipeline

# text_summary = pipeline(
#     "text-generation",
#     model="sshleifer/distilbart-cnn-12-6"
# )
# text_summary = pipeline(
#     "summarization",
#     model="sshleifer/distilbart-cnn-12-6"
# )
text_summary = pipeline(task="any-to-any", model="google/pegasus-billsum")

def summary(input_text):
    output = text_summary(input_text, max_length=100, min_length=30, do_sample=False)
    print(f"output: {output}")
    return output[0]["summary_text"]

demo = gr.Interface(
    fn=summary,
    inputs=gr.Textbox(label="Input text to summarize", lines=6),
    outputs=gr.Textbox(label="Summarized Text", lines=4),
    title="My Gen AI Practice Project 1: TEXT SUMMARIZER",
    description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT"
)

demo.launch()